license: cc-by-nc-sa-4.0
This dataset contains precomputed audio features designed for use with the openWakeWord library. Specifically, they are intended to be used as general purpose negative data (that is, data that does not contain the target wake word/phrase) for training custom openWakeWord models.
The individual .npy files in this dataset are not original audio data, but rather are low dimensional audio features produced by a pre-trained speech embedding model from Google. openWakeWord uses these features as inputs to custom word/phrase detection models.
The dataset currently contains precomputed features from the following datasets.
ACAV100M
The ACAV100M dataset contains a highly diverse set of audio data with multilingual speech, noise, music, all captured in real-world environments. This is a highly effective dataset for training custom openwakeword models.
Dataset source: https://acav100m.github.io/
Size: An array of shape (2812500, 16, 96), corresponding to ~1000 hours of audio from the ACAV100M dataset. Each row in the array has a temporal dimension of 16, which at 80 ms per temporal step results in each row containing features representing 1.28 seconds of audio.